The Energy Technologies and Systems Division at Lawrence Berkeley National Laboratory (Berkeley Lab) is inviting applications for a Postdoctoral Scholar position. The selected candidate will join the Jain (HackingMaterials) group within the Applied Energy Materials group at the frontier of autonomous science. This high-impact role bridges computational materials discovery and autonomous experimental laboratories across major initiatives including A-WILD (Genesis Mission) and PANDORA (ARPA-E).
Position Overview
| Designation | Postdoctoral Scholar |
| Research Group | Jain (HackingMaterials) Group / Applied Energy Materials Group |
| Division / Lab | Energy Technologies and Systems Division, Lawrence Berkeley National Laboratory |
| Research Area | Autonomous Science, Computational Materials Science, Machine Learning Interatomic Potentials (MLIP), First-Principles (DFT) Modeling, Catalysis & Solid-State Electrolytes |
| Location | 1 Cyclotron Road, Berkeley, CA, United States (On-site) |
| Appointment Type | Full-time, 2-year appointment (with potential for renewal) |
| Salary Range | $8,266 / month – $9,234 / month (Step-based scale governed by union contract) |
| Anticipated Start Date | November 1, 2026 |
| Last Date to Apply | Open until filled (Applications accepted until the posting is removed) |
Research Focus & Project Highlights
The candidate will contribute to two groundbreaking closed-loop discovery initiatives:
- A-WILD (AI-driven Workflows for Intelligent Lab Discovery): A DOE Genesis Mission project aimed at building a self-improving discovery engine. You will couple AI hypothesis generation with the A-Lab (Berkeley Lab’s fully autonomous inorganic synthesis laboratory), deploying simulation agents on the Genesis American Science Cloud with the Materials Project as the computational backbone.
- PANDORA: An ARPA-E-funded closed-loop AI platform focused on catalyst discovery for CO2 conversion to fuels and chemicals. You will lead computational active-site descriptor modeling, high-throughput screening using machine-learned potentials, and build a dedicated catalysis database.
Job Description & Core Responsibilities
As a Postdoctoral Scholar, your duties and scientific goals will include:
- Developing autonomous simulation agents to predict Li-ion conductivity and related transport properties, returning values, uncertainty estimates, and verifiable compute histories.
- Building and scaling MLIP/MD/DFT workflows (e.g., using atomate2, MACE, CHGNet, or UMA-class potentials) across hundreds of candidate compositions on High-Performance Computing (HPC) clusters.
- Validating theoretical predictions against thousands of real-world A-Lab experimental campaigns and integrating computational agents into live workflows via AlabOS APIs.
- Computing first-principles active-site descriptors for CO2 conversion catalysts (such as vacancy formation energies, adsorption energies, and metal-support interactions) and correlating them with empirical kinetic parameters.
- Contributing to multi-agent hypothesis generation and validation architectures alongside a curated catalysis database.
- Releasing open data, code, workflows, and benchmarks via the Materials Project and Genesis AmSC, as well as publishing findings in high-impact peer-reviewed journals.
Eligibility and Qualifications
Required Qualifications:
- Education: Ph.D. in Materials Science, Chemistry, Physics, Computer Science, or a closely related discipline.
- Postdoc Experience: Must have less than 3 years of paid postdoctoral research experience.
- Programming: Demonstrable, strong Python programming skills (a programming portfolio will be evaluated).
- Simulation Experience: Hands-on experience with Machine-Learned Interatomic Potentials (MLIPs) and Density Functional Theory (DFT) workflows (e.g., VASP, atomate2).
- HPC Proficiency: Proven experience running and scaling simulations on High-Performance Computing (HPC) architectures.
- Domain Knowledge: Broad foundational knowledge of solid-state materials science.
- Collaboration: Ability to conduct independent research within a large, interdisciplinary, multi-institutional team.
Desired Skills:
- Familiarity or direct experience with agentic frameworks and autonomous orchestration tools.
Benefits & Compensation
Berkeley Lab offers comprehensive benefits to support postdoctoral researchers and their families:
- Monthly salary starting at $8,266 to $9,234 based on experience per union salary steps.
- Comprehensive medical, dental, and vision health coverage.
- UC Defined Contribution Safe Harbor Plan and voluntary retirement savings options.
- 24 days of paid Personal Time Off (PTO) per fiscal year, plus sick leave and official holidays.
- Eight weeks of Postdoctoral Paid Family Leave.
- Active community and career advancement through the Berkeley Lab Postdoc Association.
How to Apply
Interested applicants should prepare the following documents and submit them through the official Berkeley Lab careers portal:
- Cover Letter: Detailing your research interest in the position and explaining the relevance of your background.
- Curriculum Vitae (CV) / Resume: Including publication records and a link to your programming portfolio (e.g., GitHub).
Apply Online at Berkeley Lab Careers
Application Deadline
Last Date for Apply: Applications are accepted on an ongoing basis until the posting is removed from the portal. Early application is strongly advised.
